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At least 19 recordsLinked to original sources
USGS2017

Advancing coastal ocean modelling, analysis, and prediction for the US Integrated Ocean Observing System

This paper outlines strategies that would advance coastal ocean modelling, analysis and prediction as a complement to the observing and data management activities of the coastal components of the US Integrated Ocean Observing System (IOOS®) and the Global Ocean Observing System (GOOS). The views presented are the consensus of a group of US-based researchers with a cross-section of coastal oceanography and ocean modelling expertise and community representation drawn from Regional and US Federal partners in IOOS. Priorities for research and development are suggested that would enhance the value of IOOS observations through model-based synthesis, deliver better model-based information products, and assist the design, evaluation, and operation of the observing system itself. The proposed priorities are: model coupling, data assimilation, nearshore processes, cyberinfrastructure and model skill assessment, modelling for observing system design, evaluation and operation, ensemble prediction, and fast predictors. Approaches are suggested to accomplish substantial progress in a 3–8-year timeframe. In addition, the group proposes steps to promote collaboration between research and operations groups in Regional Associations, US Federal Agencies, and the international ocean research community in general that would foster coordination on scientific and technical issues, and strengthen federal–academic partnerships benefiting IOOS stakeholders and end users.

Journal of Operational Oceanography↗
USGS2008

Ocean forecasting in terrain-following coordinates: Formulation and skill assessment of the Regional Ocean Modeling System

Systematic improvements in algorithmic design of regional ocean circulation models have led to significant enhancement in simulation ability across a wide range of space/time scales and marine system types. As an example, we briefly review the Regional Ocean Modeling System, a member of a general class of three-dimensional, free-surface, terrain-following numerical models. Noteworthy characteristics of the ROMS computational kernel include: consistent temporal averaging of the barotropic mode to guarantee both exact conservation and constancy preservation properties for tracers; redefined barotropic pressure-gradient terms to account for local variations in the density field; vertical interpolation performed using conservative parabolic splines; and higher-order, quasi-monotone advection algorithms. Examples of quantitative skill assessment are shown for a tidally driven estuary, an ice-covered high-latitude sea, a wind- and buoyancy-forced continental shelf, and a mid-latitude ocean basin. The combination of moderate-order spatial approximations, enhanced conservation properties, and quasi-monotone advection produces both more robust and accurate, and less diffusive, solutions than those produced in earlier terrain-following ocean models. Together with advanced methods of data assimilation and novel observing system technologies, these capabilities constitute the necessary ingredients for multi-purpose regional ocean prediction systems.

Journal of Computational Physics↗
USGS2024

Quantifying compound and nonlinear effects of hurricane-induced flooding using a dynamically coupled hydrological-ocean model

We recently developed a dynamically coupled hydrological-ocean modeling system that provides seamless coverage across the land-ocean continuum during hurricane-induced compound flooding. This study introduced a local inertial equation and a diagonal flow algorithm to the overland routing of the coupled system’s hydrology model (WRF-Hydro). Using Hurricane Florence (2018) as a test case, the performance of the coupled model was significantly improved, evidenced by its enhanced capability of capturing backwater and increased water level simulation accuracy and stability. With four model experiments, we present a framework to detangle, define, and quantify compound and nonlinear effects. The results revealed that the flood peaks in the lower Cape Fear River Basin and the coastal waters were contributed by inland flooding and storm surge, respectively. These two processes had comparable contributions to the flooding in the Cape Fear River Estuary. The compound effect was identified when the flood levels resulting from the combination of land and ocean processes surpassed those caused by an individual process alone. The compound effect during Hurricane Florence exhibited limited impact on flood peaks, primarily due to the time lag between the peaks of the storm surge and the inland flooding. In the period between the two peaks, the compound effect was salient and significantly impacted the magnitude and variation of the flood level. The nonlinear effect, defined as the difference between the compound flood level and the superposition of storm surge and inland flooding water levels, reduced flood levels in the river channels while increasing flood levels on the floodplain.

Water Resources Research↗
USGS2014

Advances in a distributed approach for ocean model data interoperability

An infrastructure for earth science data is emerging across the globe based on common data models and web services. As we evolve from custom file formats and web sites to standards-based web services and tools, data is becoming easier to distribute, find and retrieve, leaving more time for science. We describe recent advances that make it easier for ocean model providers to share their data, and for users to search, access, analyze and visualize ocean data using MATLAB® and Python®. These include a technique for modelers to create aggregated, Climate and Forecast (CF) metadata convention datasets from collections of non-standard Network Common Data Form (NetCDF) output files, the capability to remotely access data from CF-1.6-compliant NetCDF files using the Open Geospatial Consortium (OGC) Sensor Observation Service (SOS), a metadata standard for unstructured grid model output (UGRID), and tools that utilize both CF and UGRID standards to allow interoperable data search, browse and access. We use examples from the U.S. Integrated Ocean Observing System (IOOS®) Coastal and Ocean Modeling Testbed, a project in which modelers using both structured and unstructured grid model output needed to share their results, to compare their results with other models, and to compare models with observed data. The same techniques used here for ocean modeling output can be applied to atmospheric and climate model output, remote sensing data, digital terrain and bathymetric data.

Journal of Marine Science and Engineering↗
USGS2019

Analysis and visualization of coastal ocean model data in the cloud

The traditional flow of coastal ocean model data is from High Performance Computing (HPC) centers to the local desktop, or to a file server where just the data needed can be extracted via services such as OPeNDAP. Analysis and visualization is then conducted using local hardware and software. This requires moving large amounts of data across the internet as well as acquiring and maintaining local hardware, software and support personnel. Further, as data sets increase in size, the traditional workflow may not be scalable. Alternatively, recent advances make it possible to move data from HPC to the Cloud and perform interactive, scalable, data-proximate analysis and visualization, with simply a web browser user interface. We use the framework advanced by the NSF-funded Pangeo project, a free, open-source Python system which provides multi-user login via JupyterHub and parallel analysis via Dask, both running in Docker containers orchestrated by Kubernetes. Data is stored in the Zarr format, a Cloud-friendly ndarray format that allows performant extraction of data by anyone without relying on data services like OPeNDAP. Interactive visual exploration of data on massive model grids is made possible by new tools in the Python PyViz ecosystem, which can render maps at screen resolution, dynamically updating on pan and zoom operations. Two example are given: (1) calculating the maximum water level at each grid cell from a 53GB, 720 time step, 9 million node triangular mesh ADCIRC simulation of Hurricane Ike; (2) creating a dashboard for visualizing data from the curvilinear orthogonal COAWST/ROMS forecast model.

Journal of Marine Science and Engineering↗
USGS2015

Global climate simulations at 3000-year intervals for the last 21 000 years with the GENMOM coupled atmosphere–ocean model

We apply GENMOM, a coupled atmosphere–ocean climate model, to simulate eight equilibrium time slices at 3000-year intervals for the past 21 000 years forced by changes in Earth–Sun geometry, atmospheric greenhouse gases (GHGs), continental ice sheets, and sea level. Simulated global cooling during the Last Glacial Maximum (LGM) is 3.8 ◦C and the rate of post-glacial warming is in overall agreement with recently published temperature reconstructions. The greatest rate of warming occurs between 15 and 12 ka (2.4 ◦C over land, 0.7 ◦C over oceans, and 1.4 ◦C globally) in response to changes in radiative forcing from the diminished extent of the Northern Hemisphere (NH) ice sheets and increases in GHGs and NH summer insolation. The modeled LGM and 6 ka temperature and precipitation climatologies are generally consistent with proxy reconstructions, the PMIP2 and PMIP3 simulations, and other paleoclimate data–model analyses. The model does not capture the mid-Holocene “thermal maximum” and gradual cooling to preindustrial (PI) global temperature found in the data. Simulated monsoonal precipitation in North Africa peaks between 12 and 9 ka at values ∼ 50 % greater than those of the PI, and Indian monsoonal precipitation peaks at 12 and 9 ka at values ∼ 45 % greater than the PI. GENMOM captures the reconstructed LGM extent of NH and Southern Hemisphere (SH) sea ice. The simulated present-day Antarctica Circumpolar Current (ACC) is ∼ 48 % weaker than the observed (62 versus 119 Sv). The simulated present-day Atlantic Meridional Overturning Circulation (AMOC) of 19.3 ± 1.4 Sv on the Bermuda Rise (33◦ N) is comparable with observed value of 18.7 ± 4.8 Sv. AMOC at 33◦ N is reduced by ∼ 15 % during the LGM, and the largest post-glacial increase (∼ 11 %) occurs during the 15 ka time slice.

Climate of the Past↗
USGS2016

Technical Note: Harmonizing met-ocean model data via standard web services within small research groups

Work over the last decade has resulted in standardised web services and tools that can significantly improve the efficiency and effectiveness of working with meteorological and ocean model data. While many operational modelling centres have enabled query and access to data via common web services, most small research groups have not. The penetration of this approach into the research community, where IT resources are limited, can be dramatically improved by (1) making it simple for providers to enable web service access to existing output files; (2) using free technologies that are easy to deploy and configure; and (3) providing standardised, service-based tools that work in existing research environments. We present a simple, local brokering approach that lets modellers continue to use their existing files and tools, while serving virtual data sets that can be used with standardised tools. The goal of this paper is to convince modellers that a standardised framework is not only useful but can be implemented with modest effort using free software components. We use NetCDF Markup language for data aggregation and standardisation, the THREDDS Data Server for data delivery, pycsw for data search, NCTOOLBOX (MATLAB®) and Iris (Python) for data access, and Open Geospatial Consortium Web Map Service for data preview. We illustrate the effectiveness of this approach with two use cases involving small research modelling groups at NATO and USGS.

Ocean science and engineering↗
USGS2011

Evaluation of a present-day climate simulation with a new coupled atmosphere-ocean model GENMOM

We present a new, non-flux corrected AOGCM, GENMOM, that combines the GENESIS version 3 atmospheric GCM (Global Environmental and Ecological Simulation of Interactive Systems) and MOM2 (Modular Ocean Model version 2) nominally at T31 resolution. We evaluate GENMOM by comparison with reanalysis products (e.g., NCEP2) and three models used in the IPCC AR4 assessment. GENMOM produces a global temperature bias of 0.6 ◦C. Atmospheric features such as the jet stream structure and major semi-permanent sea level pressure centers are well simulated as is the mean planetary-scale wind structure that is needed to produce the correct position of stormtracks. Most ocean surface currents are reproduced except where they are not resolvable at T31 resolution. Overall, GENMOM captures reasonably well the observed gradients and spatial distributions of annual surface temperature and precipitation and the simulations are on par with other AOGCMs. Deficiencies in the GENMOM simulations include a warm bias in the surface temperature over the southern oceans, a split in the ITCZ and weaker-than-observed overturning circulation.

Geoscientific Model Development↗
USGS2010

Serving ocean model data on the cloud

The NOAA-led Integrated Ocean Observing System (IOOS) and the NSF-funded Ocean Observatories Initiative Cyberinfrastructure Project (OOI-CI) are collaborating on a prototype data delivery system for numerical model output and other gridded data using cloud computing. The strategy is to take an existing distributed system for delivering gridded data and redeploy on the cloud, making modifications to the system that allow it to harness the scalability of the cloud as well as adding functionality that the scalability affords.

Oceans Conference Record↗
USGS2020

Regional ocean models indicate changing limits to biological invasions in the Bering Sea

Minimal vessel traffic and cold water temperatures are believed to limit non-indigenous species (NIS) in high-latitude ecosystems. We evaluated whether suitable conditions exist in the Bering Sea for the introduction, survival, and reproduction of NIS. We compiled temperature and salinity thresholds of known NIS and compared these to ocean conditions projected during two study periods: current (2003-2012) and mid-century (2030-2039). We also explored patterns of vessel traffic and connectivity for U.S. Bering Sea ports. We found the southeastern Bering Sea had suitable conditions for the year-round survival of 80% of NIS assessed (n=42). However, only 52% of NIS had conditions suitable for reproduction or development (n=25). Conditions north of 58° N that include sub-zero winter water temperatures were unsuitable for the survival and reproduction of most NIS. While mid-century models predicted a northward expansion of suitable conditions, conditions for reproduction remained marginal. Within the highly suitable southeastern Bering Sea is the port of Dutch Harbor, which received the most vessel arrivals and ballast water discharge in the U.S. Bering Sea. Our findings illustrate the potential vulnerability of a commercially important subarctic ecosystem and highlight the need to consider NIS reproductive and developmental life phases when evaluating limits to their establishment.

ICES Journal of Marine Science↗
USGS2016

Models for ecological models: Ocean primary productivity

The ocean accounts for more than 70% of planet Earth's surface, and it processes are critically important to marine and terrestrial life. Ocean ecosystems are strongly dependent on the physical state of the ocean (e.g., transports, mixing, upwelling, runoff, and ice dynamics(. As an example, consider the Coastal Gulf of Alaska (CGOA) region.

CHANCE↗
USGS2024

Modeled coastal-ocean pathways of land-sourced contaminants in the aftermath of Hurricane Florence

Extreme precipitation during Hurricane Florence, which made landfall in North Carolina in September 2018, led to breaches of hog waste lagoons, coal ash pits, and wastewater facilities. In the weeks following the storm, freshwater discharge carried pollutants, sediment, organic matter, and debris to the coastal ocean, contributing to beach closures, algae blooms, hypoxia, and other ecosystem impacts. Here, the ocean pathways of land-sourced contaminants following Hurricane Florence are investigated using the Regional Ocean Modeling System (ROMS) with a river point source with fixed water properties from a hydrologic model (WRF-Hydro) of the Cape Fear River Basin, North Carolina's largest watershed. Patterns of contaminant transport in the coastal ocean are quantified with a finite duration tracer release based on observed flooding of agricultural and industrial facilities. A suite of synthetic events also was simulated to investigate the sensitivity of the river plume transport pathways to river discharge and wind direction. The simulated Hurricane Florence discharge event led to westward (downcoast) transport of contaminants in a coastal current, along with intermittent storage and release of material in an offshore (bulge) or eastward (upcoast) region near the river mouth, modulated by alternating upwelling and downwelling winds. The river plume patterns led to a delayed onset and long duration of contaminants affecting beaches 100 km to the west, days to weeks after the storm. Maps of the onset and duration of hypothetical water quality hazards for a range of weather conditions may provide guidance to managers on the timing of swimming/shellfishing advisories and water quality sampling.

Journal of Geophysical Research: Oceans↗
USGS2020

Wave-resolving Shoreline Boundary Conditions for Wave-Averaged Coastal Models

Downscaling broadscale ocean model information to resolve the fine-scale swash-zone dynamics has a number of applications, such as improved resolution of coastal flood hazard drivers, modeling of sediment transport and seabed morphological evolution. A new method is presented, which enables wave-averaged models for the nearshore circulation to include short-wave induced swash zone dynamics that evolve at the wave group scale (i.e. averaged over the short waves). Such dynamics, which cannot be described, by construction through wave-averaged models, play a fundamental role in nearshore hydrodynamics and morphodynamics. The method is based on the implementation of a set of Shoreline Boundary Conditions (SBCs) in wave-averaged models. The chosen set of SBCs allows for proper computation of the short-wave properties at a mean shoreline () taken as the envelope of the actual shoreline. The suitability of the approach is assessed through implementation of the SBCs into the Regional Ocean Modeling System (ROMS) coupled to a spectral wave model (InWave for IG waves and SWAN for wind waves). As the aim is to assess the viability of the approach, the SBCs are implemented only through a one-way coupling to ROMS (i.e. ROMS forcing the SBCs). Four different test cases – with constant, periodic and bichromatic offshore forcing – are run to assess the model performances. The main results of the analysis are: (a) the proposed SBCs can well reproduce the shoreline motion and swash zone dynamics in there for all chosen tests (RMSE and BIAS less than 20 % up to a cross-shore resolution of 4.0 m ( or )) and (b) implementation of the SBCs allows ROMS to accurately simulate the swash zone flows even at a resolution 40 times coarser than that needed by ROMS with its own wet–dry routine to properly describe the same flows. The latter result clearly demonstrates the major computational advantage of using the proposed SBCs. We also show that most of the swash zone dynamics is due to the mean flow (i.e. incoming Riemann variable) and the local (at ) wave height. However, especially in the case of bichromatic waves, the swash zone water volume content also seems to play a crucial role.

Ocean Modeling↗
USGS2012

Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-;atmosphere–wave–sediment transport (COAWST) modeling system

The coupled ocean–atmosphere–wave–sediment transport (COAWST) modeling system was used to investigate atmosphere–ocean–wave interactions in November 2009 during Hurricane Ida and its subsequent evolution to Nor'Ida, which was one of the most costly storm systems of the past two decades. One interesting aspect of this event is that it included two unique atmospheric extreme conditions, a hurricane and a nor'easter storm, which developed in regions with different oceanographic characteristics. Our modeled results were compared with several data sources, including GOES satellite infrared data, JASON-1 and JASON-2 altimeter data, CODAR measurements, and wave and tidal information from the National Data Buoy Center (NDBC) and the National Tidal Database. By performing a series of numerical runs, we were able to isolate the effect of the interaction terms between the atmosphere (modeled with Weather Research and Forecasting, the WRF model), the ocean (modeled with Regional Ocean Modeling System (ROMS)), and the wave propagation and generation model (modeled with Simulating Waves Nearshore (SWAN)). Special attention was given to the role of the ocean surface roughness. Three different ocean roughness closure models were analyzed: DGHQ (which is based on wave age), TY2001 (which is based on wave steepness), and OOST (which considers both the effects of wave age and steepness). Including the ocean roughness in the atmospheric module improved the wind intensity estimation and therefore also the wind waves, surface currents, and storm surge amplitude. For example, during the passage of Hurricane Ida through the Gulf of Mexico, the wind speeds were reduced due to wave-induced ocean roughness, resulting in better agreement with the measured winds. During Nor'Ida, including the wave-induced surface roughness changed the form and dimension of the main low pressure cell, affecting the intensity and direction of the winds. The combined wave age- and wave steepness-based parameterization (OOST) provided the best results for wind and wave growth prediction. However, the best agreement between the measured (CODAR) and computed surface currents and storm surge values was obtained with the wave steepness-based roughness parameterization (TY2001), although the differences obtained with respect to DGHQ were not significant. The influence of sea surface temperature (SST) fields on the atmospheric boundary layer dynamics was examined; in particular, we evaluated how the SST affects wind wave generation, surface currents and storm surges. The integrated hydrograph and integrated wave height, parameters that are highly correlated with the storm damage potential, were found to be highly sensitive to the ocean surface roughness parameterization.

Ocean Modelling↗
USGS2005

Numerical modeling of an estuary: A comprehensive skill assessment

Numerical simulations of the Hudson River estuary using a terrain-following, three-dimensional model (Regional Ocean Modeling System (ROMS)) are compared with an extensive set of time series and spatially resolved measurements over a 43 day period with large variations in tidal forcing and river discharge. The model is particularly effective at reproducing the observed temporal variations in both the salinity and current structure, including tidal, spring neap, and river discharge-induced variability. Large observed variations in stratification between neap and spring tides are captured qualitatively and quantitatively by the model. The observed structure and variations of the longitudinal salinity gradient are also well reproduced. The most notable discrepancy between the model and the data is in the vertical salinity structure. While the surface-to-bottom salinity difference is well reproduced, the stratification in the model tends to extend all the way to the water surface, whereas the observations indicate a distinct pycnocline and a surface mixed layer. Because the southern boundary coindition is located near the mouth the estuary, the salinity within the domain is particularly sensitive to the specification of salinity at the boundary. A boundary condition for the horizontal salinity gradient, based on the local value of salinity, is developed to incorporate physical processes beyond the open boundary not resolved by the model. Model results are sensitive to the specification of the bottom roughness length and vertical stability functions, insofar as they influence the intensity of vertical mixing. The results only varied slightly between different turbulence closure methods of k-??, k-??, and k-kl. Copyright 2005 by the American Geophysical Union.

New York↗
USGS2008

Development of a three-dimensional, regional, coupled wave, current, and sediment-transport model

We are developing a three-dimensional numerical model that implements algorithms for sediment transport and evolution of bottom morphology in the coastal-circulation model Regional Ocean Modeling System (ROMS v3.0), and provides a two-way link between ROMS and the wave model Simulating Waves in the Nearshore (SWAN) via the Model-Coupling Toolkit. The coupled model is applicable for fluvial, estuarine, shelf, and nearshore (surfzone) environments. Three-dimensional radiation-stress terms have been included in the momentum equations, along with effects of a surface wave roller model. The sediment-transport algorithms are implemented for an unlimited number of user-defined non-cohesive sediment classes. Each class has attributes of grain diameter, density, settling velocity, critical stress threshold for erosion, and erodibility constant. Suspended-sediment transport in the water column is computed with the same advection-diffusion algorithm used for all passive tracers and an additional algorithm for vertical settling that is not limited by the CFL criterion. Erosion and deposition are based on flux formulations. A multi-level bed framework tracks the distribution of every size class in each layer and stores bulk properties including layer thickness, porosity, and mass, allowing computation of bed morphology and stratigraphy. Also tracked are bed-surface properties including active-layer thickness, ripple geometry, and bed roughness. Bedload transport is calculated for mobile sediment classes in the top layer. Bottom-boundary layer submodels parameterize wave-current interactions that enhance bottom stresses and thereby facilitate sediment transport and increase bottom drag, creating a feedback to the circulation. The model is demonstrated in a series of simple test cases and a realistic application in Massachusetts Bay.

Computers & Geosciences↗
USGS2008

Storm-driven sediment transport in Massachusetts Bay

Massachusetts Bay is a semi-enclosed embayment in the western Gulf of Maine about 50 km wide and 100 km long. Bottom sediment resuspension is controlled predominately by storm-induced surface waves and transport by the tidal- and wind-driven circulation. Because the Bay is open to the northeast, winds from the northeast ('Northeasters') generate the largest surface waves and are thus the most effective in resuspending sediments. The three-dimensional oceanographic circulation model Regional Ocean Modeling System (ROMS) is used to explore the resuspension, transport, and deposition of sediment caused by Northeasters. The model transports multiple sediment classes and tracks the evolution of a multilevel sediment bed. The surficial sediment characteristics of the bed are coupled to one of several bottom-boundary layer modules that calculate enhanced bottom roughness due to wave-current interaction. The wave field is calculated from the model Simulating WAves Nearshore (SWAN). Two idealized simulations were carried out to explore the effects of Northeasters on the transport and fate of sediments. In one simulation, an initially spatially uniform bed of mixed sediments exposed to a series of Northeasters evolved to a pattern similar to the existing surficial sediment distribution. A second set of simulations explored sediment-transport pathways caused by storms with winds from the northeast quadrant by simulating release of sediment at selected locations. Storms with winds from the north cause transport southward along the western shore of Massachusetts Bay, while storms with winds from the east and southeast drive northerly nearshore flow. The simulations show that Northeasters can effectively transport sediments from Boston Harbor and the area offshore of the harbor to the southeast into Cape Cod Bay and offshore into Stellwagen Basin. This transport pattern is consistent with Boston Harbor as the source of silver found in the surficial sediments of Cape Cod Bay and Stellwagen Basin.

Massachusetts↗